| Cloudflare | 60.0 | 68 | 0 |
| IBM | 51.2 | 36 | 0 |
| Tidio | 49.3 | 10 | 5 |
| Palantir Technologies | 43.4 | 10 | 2 |
| Q129793 | 43.1 | 20 | 0 |
| Mistral Vibe | 41.3 | 6 | 4 |
| Tidio | 40.7 | 5 | 5 |
| Microsoft | 40.1 | 16 | 0 |
| Microsoft Dynamics | 40.1 | 16 | 0 |
| Apple Inc. | 40.0 | 0 | 107 |
| Adobe Premiere Pro | 38.4 | 14 | 0 |
| Taboola | 38.4 | 14 | 0 |
| Oracle CRM | 37.0 | 6 | 2 |
| PyTorch | 36.6 | 4 | 4 |
| Claude | 36.6 | 4 | 4 |
| Data Analytics for Machine Learning | 34.8 | 5 | 2 |
| Adobe Creative Cloud | 34.0 | 10 | 0 |
| Oracle Fusion Applications | 33.5 | 6 | 1 |
| Q207902 | 32.6 | 9 | 0 |
| Adobe Sign | 32.6 | 9 | 0 |
| Journal of Risk and Financial Management | 32.2 | 4 | 2 |
| Notion | 32.2 | 4 | 2 |
| Fivetran | 32.2 | 4 | 2 |
| n8n | 32.2 | 4 | 2 |
| CustomGPT.ai | 31.5 | 3 | 3 |
| Adobe Acrobat Reader DC | 31.1 | 8 | 0 |
| Adobe | 29.5 | 7 | 0 |
| Adobe After Effects | 29.5 | 7 | 0 |
| Adobe Photoshop Lightroom | 29.5 | 7 | 0 |
| Azure DevOps Server | 29.5 | 7 | 0 |
| Q18698690 | 29.5 | 7 | 0 |
| Zendesk | 29.3 | 2 | 4 |
| ChatGPT | 29.0 | 3 | 2 |
| Aviso AI | 29.0 | 3 | 2 |
| iTmethods Inc. | 29.0 | 3 | 2 |
| Rasa | 29.0 | 3 | 2 |
| Sage Group | 28.7 | 4 | 1 |
| Ford Motor Company | 28.2 | 0 | 26 |
| Microsoft SQL Server | 27.6 | 6 | 0 |
| Jordan/Zalaznick Advisers Inc. | 27.6 | 6 | 0 |
| Q215273 | 25.6 | 3 | 1 |
| Hugging Face | 25.6 | 3 | 1 |
| Atlan | 25.6 | 3 | 1 |
| SAP ERP | 25.4 | 5 | 0 |
| Oracle Database | 25.4 | 5 | 0 |
| Media Creation Tool | 25.4 | 5 | 0 |
| IBM Power Systems | 25.0 | 2 | 2 |
| H2O | 25.0 | 2 | 2 |
| bidirectional encoder representations from transformers | 25.0 | 2 | 2 |
| Microsoft Academic Graph | 25.0 | 2 | 2 |
| Machine Learning and Knowledge Extraction | 25.0 | 2 | 2 |
| Feast | 25.0 | 2 | 2 |
| Salesforce | 25.0 | 2 | 2 |
| GPT-4 | 25.0 | 2 | 2 |
| Dolly | 25.0 | 2 | 2 |
| Aleph Alpha | 25.0 | 2 | 2 |
| Voiceflow | 25.0 | 2 | 2 |
| Fooocus | 25.0 | 2 | 2 |
| NVIDIA Jetson Orin NX 16GB | 25.0 | 2 | 2 |
| Lyro | 25.0 | 2 | 2 |
| Microsoft Security Copilot | 25.0 | 2 | 2 |
| Reign | 25.0 | 2 | 2 |
| krish567366 / Vision-Sphere | 25.0 | 2 | 2 |
| Anove International | 25.0 | 2 | 2 |
| General Electric | 22.8 | 4 | 0 |
| Q80689 | 22.8 | 4 | 0 |
| Atlassian | 22.8 | 4 | 0 |
| Adobe Flash Player | 22.8 | 4 | 0 |
| Oracle E-Business Suite | 22.8 | 4 | 0 |
| Disease Ontology | 22.8 | 4 | 0 |
| Epic | 22.8 | 4 | 0 |
| Microsoft Movies & TV | 22.8 | 4 | 0 |
| Microsoft Lumia 640 XL | 22.8 | 4 | 0 |
| Jotform | 22.8 | 4 | 0 |
| Publications | 22.8 | 4 | 0 |
| Libertinus | 22.8 | 4 | 0 |
| Apple Intelligence | 22.5 | 0 | 13 |
| Schneider Electric | 21.5 | 2 | 1 |
| Red Hat | 21.5 | 2 | 1 |
| IBM Configuration Management Version Control | 21.5 | 2 | 1 |
| Box | 21.5 | 2 | 1 |
| Microsoft Search Server | 21.5 | 2 | 1 |
| Q21447895 | 21.5 | 2 | 1 |
| OpenAI | 21.5 | 2 | 1 |
| CaosDB - Research Data Management for Complex, Changing, and Automated Research Workflows | 21.5 | 2 | 1 |
| OneTrust | 21.5 | 2 | 1 |
| OpenAI OpCo | 21.5 | 2 | 1 |
| Freshworks | 21.5 | 2 | 1 |
| Atlas of AI, book review: Mapping out the total cost of artificial intelligence | 21.5 | 2 | 1 |
| SambaNova Systems | 21.5 | 2 | 1 |
| Hugging Face Hub | 21.5 | 2 | 1 |
| Microsoft Support | 21.5 | 2 | 1 |
| TrendMiner | 21.5 | 2 | 1 |
| vLLM | 21.5 | 2 | 1 |
| AI Assistant | 21.5 | 2 | 1 |
| Comet | 21.5 | 2 | 1 |
| krish567366 / Federated-AI-Network | 21.5 | 2 | 1 |
| Transformation Operating Framework | 21.5 | 2 | 1 |
| Microsoft Windows | 19.6 | 3 | 0 |
| JDeveloper | 19.6 | 3 | 0 |
| Jakarta EE | 19.6 | 3 | 0 |
| Adobe Audition | 19.6 | 3 | 0 |
| PricewaterhouseCoopers | 19.6 | 3 | 0 |
| Oracle SQL Developer | 19.6 | 3 | 0 |
| SAP NetWeaver Business Intelligence | 19.6 | 3 | 0 |
| Anais da Academia Brasileira de Ciências | 19.6 | 3 | 0 |
| Arquivos Brasileiros De Cardiologia | 19.6 | 3 | 0 |
| Ciência Rural | 19.6 | 3 | 0 |
| Elasticsearch | 19.6 | 3 | 0 |
| Ledger | 19.6 | 3 | 0 |
| Brazilian Dental Journal | 19.6 | 3 | 0 |
| Brazilian Journal of Chemical Engineering | 19.6 | 3 | 0 |
| Datalogix | 19.6 | 3 | 0 |
| IBM Bluemix | 19.6 | 3 | 0 |
| Microsoft Lumia 640 | 19.6 | 3 | 0 |
| G2 | 19.6 | 3 | 0 |
| Dataiku | 19.6 | 3 | 0 |
| Clinics | 19.6 | 3 | 0 |
| Revista brasileira de hematologia e hemoterapia | 19.6 | 3 | 0 |
| The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases | 19.6 | 3 | 0 |
| Brazilian Journal of Poultry Science | 19.6 | 3 | 0 |
| Revista brasileira de sementes = Brazilian seed journal | 19.6 | 3 | 0 |
| Revista Brasileira de fruticultura | 19.6 | 3 | 0 |
| International Journal of Neonatal Screening | 19.6 | 3 | 0 |
| InfraKit | 19.6 | 3 | 0 |
| Oracle ERP Cloud | 19.6 | 3 | 0 |
| Oracle Cloud Platform | 19.6 | 3 | 0 |
| Revista de Microbiologia | 19.6 | 3 | 0 |
| Oracle HCM Cloud | 19.6 | 3 | 0 |
| Microsoft Docs | 19.6 | 3 | 0 |
| Education (Basel) | 19.6 | 3 | 0 |
| emacs-gnuplot | 19.6 | 3 | 0 |
| HealthHero | 19.6 | 3 | 0 |
| Microsoft Learn | 19.6 | 3 | 0 |
| Microsoft Typography | 19.6 | 3 | 0 |
| WinCC | 19.2 | 1 | 2 |
| Artificial Intelligence | 19.2 | 1 | 2 |
| TensorFlow.js | 19.2 | 1 | 2 |
| Airbnb | 18.8 | 0 | 8 |
| Tesla | 16.6 | 0 | 6 |
| Contentsquare | 16.6 | 0 | 6 |
| Rudrendu Kumar Paul | 16.6 | 0 | 6 |
| French Wikipedia | 15.7 | 1 | 1 |
| SAS Institute | 15.7 | 1 | 1 |
| Rockwell Automation | 15.7 | 1 | 1 |
| Adobe Media Server | 15.7 | 1 | 1 |
| Microsoft Knowledge Base | 15.7 | 1 | 1 |
| Automated Testing Framework | 15.7 | 1 | 1 |
| Fractal Analytics | 15.7 | 1 | 1 |
| Genesys | 15.7 | 1 | 1 |
| RightNow Technologies | 15.7 | 1 | 1 |
| Windmill | 15.7 | 1 | 1 |
| Crunchbase | 15.7 | 1 | 1 |
| Uptake | 15.7 | 1 | 1 |
| Tape | 15.7 | 1 | 1 |
| Dataminr | 15.7 | 1 | 1 |
| Google | 15.7 | 1 | 1 |
| GitHub | 15.6 | 2 | 0 |
| Q11219 | 15.6 | 2 | 0 |
| Q11278 | 15.6 | 2 | 0 |
| Cornell University | 15.6 | 2 | 0 |
| Microsoft Money | 15.6 | 2 | 0 |
| Intel Technology Journal | 15.6 | 2 | 0 |
| Adobe Digital Editions | 15.6 | 2 | 0 |
| Windows Glyph List 4 | 15.6 | 2 | 0 |
| Windows Installer | 15.6 | 2 | 0 |
| SPSS | 15.6 | 2 | 0 |
| Nvidia | 15.6 | 2 | 0 |
| DirectX | 15.6 | 2 | 0 |
| JPMorgan Chase | 15.6 | 2 | 0 |
| Adobe Dreamweaver | 15.6 | 2 | 0 |
| Robert Bosch | 15.6 | 2 | 0 |
| Wolters Kluwer | 15.6 | 2 | 0 |
| PCMan File Manager | 15.6 | 2 | 0 |
| IFS AB | 15.6 | 2 | 0 |
| DELMIA | 15.6 | 2 | 0 |
| Programme for International Student Assessment | 15.6 | 2 | 0 |
| Microsoft Paint | 15.6 | 2 | 0 |
| Acta Botanica Brasilica | 15.6 | 2 | 0 |
| Akamai Technologies | 15.6 | 2 | 0 |
| CHKDSK | 15.6 | 2 | 0 |
| Microsoft Digital Image | 15.6 | 2 | 0 |
| Windows Registry | 15.6 | 2 | 0 |
| Ernst & Young | 15.6 | 2 | 0 |
| Deloitte | 15.6 | 2 | 0 |
| KPMG | 15.6 | 2 | 0 |
| Veritas Software | 15.6 | 2 | 0 |
| Software AG | 15.6 | 2 | 0 |
| Tom's Hardware | 15.6 | 2 | 0 |
| OCRopus | 15.6 | 2 | 0 |
| Autodesk | 15.6 | 2 | 0 |
| Visual Basic for Applications | 15.6 | 2 | 0 |
| Microsoft Dynamics AX | 15.6 | 2 | 0 |
| PhysX | 15.6 | 2 | 0 |
| Azure | 15.6 | 2 | 0 |
| Alvaria | 15.6 | 2 | 0 |
| Elsevier | 15.6 | 2 | 0 |
| Windows Virtual PC | 15.6 | 2 | 0 |
| Windows Essentials | 15.6 | 2 | 0 |
| Forrester | 15.6 | 2 | 0 |
| Honeywell | 15.6 | 2 | 0 |
| Microsoft Dynamics NAV | 15.6 | 2 | 0 |
| Microsoft AutoRoute | 15.6 | 2 | 0 |
| Salesforce | 15.6 | 2 | 0 |
| Adobe LiveCycle Designer | 15.6 | 2 | 0 |
| IBM Informix | 15.6 | 2 | 0 |
| util-linux | 15.6 | 2 | 0 |
| Lightbeam (software) | 15.6 | 2 | 0 |
| CICS | 15.6 | 2 | 0 |
| IBM Rational DOORS | 15.6 | 2 | 0 |
| Intelligent Input Bus | 15.6 | 2 | 0 |
| Microsoft Dynamics GP | 15.6 | 2 | 0 |
| Snipping Tool | 15.6 | 2 | 0 |
| Microsoft Virtual Server | 15.6 | 2 | 0 |
| Intuit | 15.6 | 2 | 0 |
| Sound Recorder | 15.6 | 2 | 0 |
| MIT Media Lab | 15.6 | 2 | 0 |
| Adobe FrameMaker | 15.6 | 2 | 0 |
| GFT Technologies | 15.6 | 2 | 0 |
| Telephony Application Programming Interface | 15.6 | 2 | 0 |
| TIBCO Spotfire Analytics | 15.6 | 2 | 0 |
| Splunk Inc. | 15.6 | 2 | 0 |
| Rational Rhapsody | 15.6 | 2 | 0 |
| Oracle Application Server | 15.6 | 2 | 0 |
| Heart Rhythm | 15.6 | 2 | 0 |
| NetBackup | 15.6 | 2 | 0 |
| Gummi | 15.6 | 2 | 0 |
| Siebel Systems | 15.6 | 2 | 0 |
| Business Standard | 15.6 | 2 | 0 |
| CPLEX | 15.6 | 2 | 0 |
| TALIS | 15.6 | 2 | 0 |
| Microsoft Student | 15.6 | 2 | 0 |
| Brazilian Journal of Physics | 15.6 | 2 | 0 |
| ZDNET | 15.6 | 2 | 0 |
| Vantive | 15.6 | 2 | 0 |
| Adobe LiveMotion | 15.6 | 2 | 0 |
| Wolters Kluwer Deutschland | 15.6 | 2 | 0 |
| Scientia Agricola | 15.6 | 2 | 0 |
| Bioorganic & Medicinal Chemistry Letters | 15.6 | 2 | 0 |
| Adobe Content Server | 15.6 | 2 | 0 |
| AutoCAD Architecture | 15.6 | 2 | 0 |
| Automattic | 15.6 | 2 | 0 |
| OpenShift | 15.6 | 2 | 0 |
| Entropy | 15.6 | 2 | 0 |
| Electrochimica Acta | 15.6 | 2 | 0 |
| Eclética Química | 15.6 | 2 | 0 |
| EDGAR | 15.6 | 2 | 0 |
| OmniPage | 15.6 | 2 | 0 |
| Microsoft Layer for Unicode | 15.6 | 2 | 0 |
| Autodesk MotionBuilder | 15.6 | 2 | 0 |
| uPortal | 15.6 | 2 | 0 |
| Dymola | 15.6 | 2 | 0 |
| Creatio | 15.6 | 2 | 0 |
| Q4052640 | 15.6 | 2 | 0 |
| Yahoo! Finance | 15.6 | 2 | 0 |
| Adobe Animate | 15.6 | 2 | 0 |
| Electronic Privacy Information Center | 15.6 | 2 | 0 |
| BIOVIA | 15.6 | 2 | 0 |
| Adobe RoboHelp | 15.6 | 2 | 0 |
| Adobe eLearning Suite | 15.6 | 2 | 0 |
| athenahealth | 15.6 | 2 | 0 |
| Beebdroid | 15.6 | 2 | 0 |
| Coveo | 15.6 | 2 | 0 |
| Energies | 15.6 | 2 | 0 |
| Frege | 15.6 | 2 | 0 |
| Genes | 15.6 | 2 | 0 |
| Brazilian Journal of Biology | 15.6 | 2 | 0 |
| HubSpot | 15.6 | 2 | 0 |
| IntelliType | 15.6 | 2 | 0 |
| International Journal of Environmental Research and Public Health | 15.6 | 2 | 0 |
| Revista Brasileira de Biologia | 15.6 | 2 | 0 |
| Java BluePrints | 15.6 | 2 | 0 |
| Lebensmittel-Wissenschaft & Technologie | 15.6 | 2 | 0 |
| Liveperson Inc. | 15.6 | 2 | 0 |
| Machine Design | 15.6 | 2 | 0 |
| Marketo | 15.6 | 2 | 0 |
| Materials | 15.6 | 2 | 0 |
| Intel oneAPI Math Kernel Library | 15.6 | 2 | 0 |
| MEDIDATA Solutions | 15.6 | 2 | 0 |
| Microsoft Japan | 15.6 | 2 | 0 |
| Neotropical Ichthyology | 15.6 | 2 | 0 |
| Nimble Storage | 15.6 | 2 | 0 |
| Nutrients | 15.6 | 2 | 0 |
| Office of the National Coordinator for Health Information Technology | 15.6 | 2 | 0 |
| Oracle Property Manager | 15.6 | 2 | 0 |
| Owl Lisp | 15.6 | 2 | 0 |
| Primary Children's Medical Center | 15.6 | 2 | 0 |
| QuickBooks | 15.6 | 2 | 0 |
| Red Hat Virtualization | 15.6 | 2 | 0 |
| Revista Brasileira de Estudos de População | 15.6 | 2 | 0 |
| Brazilian Journal of Psychiatry | 15.6 | 2 | 0 |
| RingCentral | 15.6 | 2 | 0 |
| Scientia Pharmaceutica | 15.6 | 2 | 0 |
| Viruses | 15.6 | 2 | 0 |
| Workday, Inc. | 15.6 | 2 | 0 |
| World Psychiatry | 15.6 | 2 | 0 |
| Zscaler | 15.6 | 2 | 0 |
| Revista Brasileira de Ciências Sociais | 15.6 | 2 | 0 |
| Revista Brasileira de Ensino de Física | 15.6 | 2 | 0 |
| Q10984556 | 15.6 | 2 | 0 |
| Microsoft Pinyin IME | 15.6 | 2 | 0 |
| AutoKey | 15.6 | 2 | 0 |
| Toxins | 15.6 | 2 | 0 |
| Journal of Applied Oral Science | 15.6 | 2 | 0 |
| Arquivos de Neuro-Psiquiatria | 15.6 | 2 | 0 |
| Agora | 15.6 | 2 | 0 |
| Pharmaceuticals | 15.6 | 2 | 0 |
| Arquivos Brasileiros de Endocrinologia e Metabologia | 15.6 | 2 | 0 |
| Arquivos de Gastroenterologia | 15.6 | 2 | 0 |
| Arquivos Brasileiros de Oftalmologia | 15.6 | 2 | 0 |
| Arquivo Brasileiro de Medicina Veterinaria e Zootecnia | 15.6 | 2 | 0 |
| Kriterion: revista de filosofia | 15.6 | 2 | 0 |
| Alea | 15.6 | 2 | 0 |
| Bragantia | 15.6 | 2 | 0 |
| Ciencia e Tecnologia de Alimentos | 15.6 | 2 | 0 |
| Journal of Manufacturing Systems | 15.6 | 2 | 0 |
| Revista Brasileira de Zootecnia | 15.6 | 2 | 0 |
| Revista Latino-Americana de Efermagem | 15.6 | 2 | 0 |
| Revista de Psiquiatria Clinica | 15.6 | 2 | 0 |
| Brazilian Journal of Microbiology | 15.6 | 2 | 0 |
| Mana | 15.6 | 2 | 0 |
| Revista Brasileira de Entomologia | 15.6 | 2 | 0 |
| Memórias do Instituto Oswaldo Cruz | 15.6 | 2 | 0 |
| Iheringia. Série Zoologia | 15.6 | 2 | 0 |
| Neotropical Entomology | 15.6 | 2 | 0 |
| Sao Paulo Medical Journal | 15.6 | 2 | 0 |
| Sustainability | 15.6 | 2 | 0 |
| Water | 15.6 | 2 | 0 |
| Revista Arvore: Brazilian Journal of Forest Science | 15.6 | 2 | 0 |
| Akka | 15.6 | 2 | 0 |
| National Health Service | 15.6 | 2 | 0 |
| Microsoft Mobile | 15.6 | 2 | 0 |
| Remote Sensing | 15.6 | 2 | 0 |
| Adobe for Business | 15.6 | 2 | 0 |
| Microsoft Dynamics SL | 15.6 | 2 | 0 |
| Life | 15.6 | 2 | 0 |
| Comm100 Live Chat | 15.6 | 2 | 0 |
| Xactly Corporation | 15.6 | 2 | 0 |
| OECD Main Economic Indicators | 15.6 | 2 | 0 |
| Biology | 15.6 | 2 | 0 |
| Q18146823 | 15.6 | 2 | 0 |
| Q18168774 | 15.6 | 2 | 0 |
| Performance Analyzer | 15.6 | 2 | 0 |
| Sprinklr | 15.6 | 2 | 0 |
| Luton and Dunstable University Hospital NHS Foundation Trust | 15.6 | 2 | 0 |
| Oracle BlueKai Data Management Platform | 15.6 | 2 | 0 |
| Nauplius | 15.6 | 2 | 0 |
| Insects | 15.6 | 2 | 0 |
| Microsoft Lumia 950 XL | 15.6 | 2 | 0 |
| Data Analytics Library | 15.6 | 2 | 0 |
| HashiCorp | 15.6 | 2 | 0 |
| SAP S/4HANA | 15.6 | 2 | 0 |
| Maps | 15.6 | 2 | 0 |
| Elastic | 15.6 | 2 | 0 |
| Kaminari | 15.6 | 2 | 0 |
| Chakra | 15.6 | 2 | 0 |
| Windows Subsystem for Linux | 15.6 | 2 | 0 |
| Biomolecules | 15.6 | 2 | 0 |
| Adobe XD | 15.6 | 2 | 0 |
| Microsoft Entra ID | 15.6 | 2 | 0 |
| Azure Cognitive Search | 15.6 | 2 | 0 |
| Pró-fono : revista de atualização científica | 15.6 | 2 | 0 |
| Cadernos de saúde pública | 15.6 | 2 | 0 |
| Jornal de pediatria | 15.6 | 2 | 0 |
| International Brazilian Journal of Urology | 15.6 | 2 | 0 |
| Revista do Instituto de Medicina Tropical de São Paulo | 15.6 | 2 | 0 |
| Medicina | 15.6 | 2 | 0 |
| Revista da Associação Médica Brasileira | 15.6 | 2 | 0 |
| Revista da Sociedade Brasileira de Medicina Tropical | 15.6 | 2 | 0 |
| Ciência & saude coletiva | 15.6 | 2 | 0 |
| Revista brasileira de anestesiologia | 15.6 | 2 | 0 |
| Revista brasileira de ginecologia e obstetrícia : revista da Federação Brasileira das Sociedades de Ginecologia e Obstetrícia | 15.6 | 2 | 0 |
| Brazilian Oral Research | 15.6 | 2 | 0 |
| Microsoft Dynamics 365 | 15.6 | 2 | 0 |
| Revista de odontologia da Universidade de Sao Paulo | 15.6 | 2 | 0 |
| Revista do Hospital das Clinicas | 15.6 | 2 | 0 |
| História, Ciências, Saúde-Manguinhos | 15.6 | 2 | 0 |
| Pesquisa Odontológica Brasileira | 15.6 | 2 | 0 |
| Revista brasileira de ciencia do solo | 15.6 | 2 | 0 |
| Brazilian Journal of Botany | 15.6 | 2 | 0 |
| Psicologia em estudo | 15.6 | 2 | 0 |
| Diversity | 15.6 | 2 | 0 |
| Tempo (Rio de Janeiro, Brazil) | 15.6 | 2 | 0 |
| Cancers | 15.6 | 2 | 0 |
| Techniques in gastrointestinal endoscopy | 15.6 | 2 | 0 |
| Pharmaceutics | 15.6 | 2 | 0 |
| Atmosphere | 15.6 | 2 | 0 |
| Journal of Functional Biomaterials | 15.6 | 2 | 0 |
| Behavioral Sciences | 15.6 | 2 | 0 |
| Membranes | 15.6 | 2 | 0 |
| Metabolites | 15.6 | 2 | 0 |
| Symmetry | 15.6 | 2 | 0 |
| Antibodies | 15.6 | 2 | 0 |
| Plants | 15.6 | 2 | 0 |
| Pathogens | 15.6 | 2 | 0 |
| Brain Sciences | 15.6 | 2 | 0 |
| Metals | 15.6 | 2 | 0 |
| Journal of Marine Science and Engineering | 15.6 | 2 | 0 |
| Cells | 15.6 | 2 | 0 |
| Journal of Personalized Medicine | 15.6 | 2 | 0 |
| Journal of Clinical Medicine | 15.6 | 2 | 0 |
| Brazilian journal of veterinary research and animal science | 15.6 | 2 | 0 |
| Biosensors | 15.6 | 2 | 0 |
| Nanomaterials | 15.6 | 2 | 0 |
| Geosciences | 15.6 | 2 | 0 |
| Journal of Developmental Biology | 15.6 | 2 | 0 |
| Educacao & sociedade | 15.6 | 2 | 0 |
| Proteomes | 15.6 | 2 | 0 |
| Religions | 15.6 | 2 | 0 |
| International Journal of Geo Information | 15.6 | 2 | 0 |
| Administrative Sciences | 15.6 | 2 | 0 |
| Microorganisms | 15.6 | 2 | 0 |
| Photonics | 15.6 | 2 | 0 |
| Medical Sciences | 15.6 | 2 | 0 |
| Electronics | 15.6 | 2 | 0 |
| Vaccines | 15.6 | 2 | 0 |
| Societies | 15.6 | 2 | 0 |
| Applied Sciences | 15.6 | 2 | 0 |
| Land | 15.6 | 2 | 0 |
| Animals | 15.6 | 2 | 0 |
| Journal of Intelligence | 15.6 | 2 | 0 |
| Actuators | 15.6 | 2 | 0 |
| Diseases | 15.6 | 2 | 0 |
| Antibiotics | 15.6 | 2 | 0 |
| Toxics | 15.6 | 2 | 0 |
| Social Sciences | 15.6 | 2 | 0 |
| Micromachines | 15.6 | 2 | 0 |
| Children | 15.6 | 2 | 0 |
| Journal of Cardiovascular Development and Disease | 15.6 | 2 | 0 |
| Non-Coding RNA | 15.6 | 2 | 0 |
| Processes | 15.6 | 2 | 0 |
| Diagnostics | 15.6 | 2 | 0 |
| Forests | 15.6 | 2 | 0 |
| Laws | 15.6 | 2 | 0 |
| Healthcare | 15.6 | 2 | 0 |
| Minerals | 15.6 | 2 | 0 |
| Jornal brasileiro de patologia e medicina laboratorial | 15.6 | 2 | 0 |
| Antioxidants | 15.6 | 2 | 0 |
| Foods | 15.6 | 2 | 0 |
| Medicines | 15.6 | 2 | 0 |
| Agronomy | 15.6 | 2 | 0 |
| Crystals | 15.6 | 2 | 0 |
| Informatics | 15.6 | 2 | 0 |
| Bioengineering | 15.6 | 2 | 0 |
| Fibers | 15.6 | 2 | 0 |
| Chemosensors | 15.6 | 2 | 0 |
| Pharmacy | 15.6 | 2 | 0 |
| Veterinary Sciences | 15.6 | 2 | 0 |
| Atoms | 15.6 | 2 | 0 |
| Cosmetics | 15.6 | 2 | 0 |
| Separations | 15.6 | 2 | 0 |
| Technologies | 15.6 | 2 | 0 |
| Axios | 15.6 | 2 | 0 |
| Forbes 30 Under 30 | 15.6 | 2 | 0 |
| Educação em Revista | 15.6 | 2 | 0 |
| Future Internet | 15.6 | 2 | 0 |
| Data | 15.6 | 2 | 0 |
| Bubble | 15.6 | 2 | 0 |
| cligh | 15.6 | 2 | 0 |
| hidapi | 15.6 | 2 | 0 |
| libtelnet | 15.6 | 2 | 0 |
| llvm-libunwind | 15.6 | 2 | 0 |
| os-diskconfig-python-novaclient-ext | 15.6 | 2 | 0 |
| python-scsi | 15.6 | 2 | 0 |
| ucpp | 15.6 | 2 | 0 |
| Risks | 15.6 | 2 | 0 |
| Microsoft Dynamics 365 for Finance and Operations | 15.6 | 2 | 0 |
| MPDV Mikrolab (Germany) | 15.6 | 2 | 0 |
| Boscombe Community Hospital | 15.6 | 2 | 0 |
| Optum | 15.6 | 2 | 0 |
| Prometeia | 15.6 | 2 | 0 |
| MDPI | 15.6 | 2 | 0 |
| SAS Institute | 15.6 | 2 | 0 |
| TheGuardian.com | 15.3 | 0 | 5 |
| Rollo | 15.3 | 0 | 5 |
| Nayan Goel | 15.3 | 0 | 5 |
| BaiduWiki | 15.3 | 0 | 5 |
| CNN.com | 13.7 | 0 | 4 |
| Data transformation and knowledge retrieval for humanitarian crisis response | 13.7 | 0 | 4 |
| Medical AI Security and Data Privacy in the Age of Computer Vision | 13.7 | 0 | 4 |
| Industry 4.0 oriented predictive analytics of cardiovascular diseases using machine learning, hyperparameter tuning and ensemble techniques | 13.7 | 0 | 4 |
| Machine learning based concept drift detection for predictive maintenance | 13.7 | 0 | 4 |
| Anomaly Detection In IoT Sensor Data Using Machine Learning Techniques For Predictive Maintenance In Smart Grids | 13.7 | 0 | 4 |
| AI agent | 13.7 | 0 | 4 |
| SENTIMENT ANALYSIS IN SOCIAL MEDIA: HOW DATA SCIENCE IMPACTS PUBLIC OPINION KNOWLEDGE INTEGRATES NATURAL LANGUAGE PROCESSING (NLP) WITH ARTIFICIAL INTELLIGENCE (AI) | 13.7 | 0 | 4 |
| AI-Enabled Smart System for Continuous Monitoring of Neonatal Vital Signs in Intensive Care Unit | 13.7 | 0 | 4 |
| Merehead | 13.7 | 0 | 4 |
| klapa.hr | 13.7 | 0 | 4 |
| SOFI AI Tech Solution Inc. | 13.7 | 0 | 4 |
| Lebara Group | 11.8 | 0 | 3 |
| predictive maintenance | 11.8 | 0 | 3 |
| JAMA Surgery | 11.8 | 0 | 3 |
| Coherent Solutions | 11.8 | 0 | 3 |
| enterprise information security architecture | 11.8 | 0 | 3 |
| Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 11.8 | 0 | 3 |
| operational risk management | 11.8 | 0 | 3 |
| Eric P. Xing | 11.8 | 0 | 3 |
| Perspectives in healthcare risk management | 11.8 | 0 | 3 |
| Proceedings. IEEE Workshop on Applications of Computer Vision | 11.8 | 0 | 3 |
| Quality assurance, quality management or quality control? | 11.8 | 0 | 3 |
| Quantitative research versus quality assurance, quality improvement, total quality management, and continuous quality improvement | 11.8 | 0 | 3 |
| Machine learning in cell biology – teaching computers to recognize phenotypes | 11.8 | 0 | 3 |
| Deepening our understanding of quality improvement in Europe (DUQuE): overview of a study of hospital quality management in seven countries | 11.8 | 0 | 3 |
| Perspectives on Quality Control, Risk Management, and Analytical Quality Management | 11.8 | 0 | 3 |
| Quality assurance in the mycobacteriology laboratory. Quality control, quality improvement, and proficiency testing | 11.8 | 0 | 3 |
| Artificial Intelligence in Medical Practice: The Question to the Answer? | 11.8 | 0 | 3 |
| Machine learning-based detection of chemical risk | 11.8 | 0 | 3 |
| Clinical leadership: using observations of care to focus risk management and quality improvement activities in the clinical setting | 11.8 | 0 | 3 |
| Data Science: Big Data, Machine Learning, and Artificial Intelligence | 11.8 | 0 | 3 |
| Real-time monitoring of clinical processes using complex event processing and transition systems | 11.8 | 0 | 3 |
| DuerOS | 11.8 | 0 | 3 |
| Machine learning in computer vision | 11.8 | 0 | 3 |
| Robotics and computer vision techniques combined with non-invasive consumer biometrics to assess quality traits from beer foamability using machine learning: A potential for artificial intelligence applications | 11.8 | 0 | 3 |
| Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation | 11.8 | 0 | 3 |
| Quality assurance, quality management, risk management, and other buzz words of the eighties. How do we use them? | 11.8 | 0 | 3 |
| Integrating quality assurance and total quality management/quality improvement | 11.8 | 0 | 3 |
| Deep Learning for Industrial Computer Vision Quality Control in the Printing Industry 4.0. | 11.8 | 0 | 3 |
| Automated Detection of Radiology Reports that Require Follow-up Imaging Using Natural Language Processing Feature Engineering and Machine Learning Classification | 11.8 | 0 | 3 |
| Quality Control, Quality Assurance, and Quality Improvement-What is the Difference and Why Should Compounding Pharmacies Care? | 11.8 | 0 | 3 |
| Q97454550 | 11.8 | 0 | 3 |
| Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation Study | 11.8 | 0 | 3 |
| Artificial Intelligence Applications for Workflow, Process Optimization and Predictive Analytics | 11.8 | 0 | 3 |
| Kairntech SAS | 11.8 | 0 | 3 |
| Stochastic Channel-Based Federated Learning With Neural Network Pruning for Medical Data Privacy Preservation: Model Development and Experimental Validation | 11.8 | 0 | 3 |
| PolyAnalyst | 11.8 | 0 | 3 |
| A Study Using Artificial Intelligence to Identify Adults With Complex Perianal Fistulas Associated With Crohn's Disease | 11.8 | 0 | 3 |
| AI@Centech | 11.8 | 0 | 3 |
| Machine learning in coupled wildfire-water supply risk assessment: Data science toolkit | 11.8 | 0 | 3 |
| Machine learning, artificial intelligence, and data science breaking into drug design and neglected diseases | 11.8 | 0 | 3 |
| prompt engineering | 11.8 | 0 | 3 |
| Vision and Language | 11.8 | 0 | 3 |
| Cloud-based data pipeline orchestration platform for COVID-19 evidence-based analytics | 11.8 | 0 | 3 |
| Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future | 11.8 | 0 | 3 |
| foundation model | 11.8 | 0 | 3 |
| Sri Priya Ponnapalli | 11.8 | 0 | 3 |
| Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence | 11.8 | 0 | 3 |
| Intelligent Single-Board Computer for Industry 4.0: Efficient Real-Time Monitoring System for Anomaly Detection in CNC Machines | 11.8 | 0 | 3 |
| Artificial Intelligence as a Process Optimization Driver under Industry 4.0 Framework and the Role of IIoT, a Bibliometric Analysis | 11.8 | 0 | 3 |
| SmartAirQ: A Big Data Governance Framework for Urban Air Quality Management in Smart Cities | 11.8 | 0 | 3 |
| Federated learning algorithm based on matrix mapping for data privacy over edge computing | 11.8 | 0 | 3 |
| A Digital Twin Based Industrial Automation and Control System Security Architecture | 11.8 | 0 | 3 |
| From distributed machine learning to federated learning: In the view of data privacy and security | 11.8 | 0 | 3 |
| Artificial intelligence-based condition monitoring and predictive maintenance framework for wind turbines | 11.8 | 0 | 3 |
| ICS for multivariate functional anomaly detection with applications to predictive maintenance and quality control | 11.8 | 0 | 3 |
| conversational AI | 11.8 | 0 | 3 |
| Anomaly detection and troubleshooting system for a network using machine learning and/or artificial intelligence | 11.8 | 0 | 3 |
| Implementing artificial intelligence agents to perform machine learning tasks using predictive analytics to leverage ensemble policies for maximizing | 11.8 | 0 | 3 |
| Machine learning model development with interactive model evaluation | 11.8 | 0 | 3 |
| Artificial intelligence and machine learning based product development | 11.8 | 0 | 3 |
| Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence | 11.8 | 0 | 3 |
| SinaLab | 11.8 | 0 | 3 |
| retrieval-augmented generation | 11.8 | 0 | 3 |
| Applied artificial intelligence technology for building a knowledge base using natural language processing | 11.8 | 0 | 3 |
| Artificial intelligence for health message generation: an empirical study using a large language model (LLM) and prompt engineering | 11.8 | 0 | 3 |
| Towards syntax-aware pretraining and prompt engineering for knowledge retrieval from large language models | 11.8 | 0 | 3 |
| Mapping the Role and Impact of Artificial Intelligence and Machine Learning Applications in Supply Chain Digital Transformation: A Bibliometric Analysis | 11.8 | 0 | 3 |
| In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning | 11.8 | 0 | 3 |
| PNS266 LANDSCAPE ANALYSIS OF IMPACT OF MACHINE LEARNING, NATURAL LANGUAGE PROCESSING, ARTIFICIAL INTELLIGENCE AND BLOCKCHAIN TECHNOLOGY ON LEVERAGING REAL WORLD EVIDENCE (RWE) | 11.8 | 0 | 3 |
| Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry | 11.8 | 0 | 3 |
| Sentiment Analysis in Product Reviews using Natural Language Processing and Machine Learning | 11.8 | 0 | 3 |
| Concept Drift Detection and Adaption in Big Imbalance Industrial IoT Data Using an Ensemble Learning Method of Offline Classifiers | 11.8 | 0 | 3 |
| The quality management ecosystem for predictive maintenance in the Industry 4.0 era | 11.8 | 0 | 3 |
| Practical AI: Machine Learning, Data Science | 11.8 | 0 | 3 |
| Anomaly detection system for data quality assurance in IoT infrastructures based on machine learning | 11.8 | 0 | 3 |
| Resource Efficient Federated Learning and DAG Blockchain With Sharding in Digital Twin Driven Industrial IoT | 11.8 | 0 | 3 |
| Digital transformation: An empirical analysis of operational efficiency, customer experience, and competitive advantage in Jordanian Islamic banks | 11.8 | 0 | 3 |
| Customer support ticket escalation prediction using feature engineering | 11.8 | 0 | 3 |
| Expert Monitoring: Human-Centered Concept Drift Detection in Machine Learning Operations | 11.8 | 0 | 3 |
| Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios | 11.8 | 0 | 3 |
| Application of Artificial Intelligence in Condition Monitoring and Predictive Maintenance of Rail Transit Vehicle Equipment | 11.8 | 0 | 3 |
| Alfred Zimmermann | 11.8 | 0 | 3 |
| SentemQC - A novel and cost-efficient method for quality assurance and quality control of high-resolution frequency sensor data in fresh waters | 11.8 | 0 | 3 |
| Model AI Governance Framework for Generative AI | 11.8 | 0 | 3 |
| Vanta | 11.8 | 0 | 3 |
| Tidio Copilot | 11.8 | 0 | 3 |
| Q136153857 | 11.8 | 0 | 3 |
| Q136467205 | 11.8 | 0 | 3 |
| Q136833308 | 11.8 | 0 | 3 |
| Toward Greener Matrix Operations by Lossless Compressed Formats | 11.8 | 0 | 3 |
| AI Genesis | 11.8 | 0 | 3 |
| technovedaai | 11.8 | 0 | 3 |
| AiiACo | 11.8 | 0 | 3 |
| Aona AI | 11.8 | 0 | 3 |
| Victor Hugo Villafañe Aguilar | 11.8 | 0 | 3 |
| Konecto | 11.8 | 0 | 3 |
| Artificial Intelligence and Machine Learning in Telecommunications Revolutionizing Customer Experience and Enhancing Service Delivery | 11.8 | 0 | 3 |
| geogen gialon | 11.8 | 0 | 3 |
| Wittify | 11.8 | 0 | 3 |
| digitalhumanOS | 11.8 | 0 | 3 |
| Digital Clouds | 11.8 | 0 | 3 |
| Text | 11.8 | 0 | 3 |
| Production-Grade Agentic AI | 11.8 | 0 | 3 |
| Ani Catino | 11.8 | 0 | 3 |
| iTuring.ai | 11.8 | 0 | 3 |
| Hello Patient | 11.8 | 0 | 3 |
| Assistable | 11.8 | 0 | 3 |
| Surogate | 11.8 | 0 | 3 |
| T3A | 11.8 | 0 | 3 |
| The Independent | 9.4 | 0 | 2 |
| artificial intelligence | 9.4 | 0 | 2 |
| Peter Norvig | 9.4 | 0 | 2 |
| Donald Michie | 9.4 | 0 | 2 |
| emerging technology | 9.4 | 0 | 2 |
| Microsoft Bing | 9.4 | 0 | 2 |
| Q207708 | 9.4 | 0 | 2 |
| sales planning | 9.4 | 0 | 2 |
| computer-aided quality assurance | 9.4 | 0 | 2 |
| Andreas Holzinger | 9.4 | 0 | 2 |
| Microsoft Identity Integration Server | 9.4 | 0 | 2 |
| single sign-on | 9.4 | 0 | 2 |
| Knowledge Engineering and Machine Learning Group | 9.4 | 0 | 2 |
| Spotify | 9.4 | 0 | 2 |
| Atlantic Council | 9.4 | 0 | 2 |
| quality management | 9.4 | 0 | 2 |
| backpropagation | 9.4 | 0 | 2 |
| intelligent control | 9.4 | 0 | 2 |
| quality assurance | 9.4 | 0 | 2 |
| Netflix | 9.4 | 0 | 2 |
| certification mark | 9.4 | 0 | 2 |
| Capital One | 9.4 | 0 | 2 |
| natural language understanding | 9.4 | 0 | 2 |
| principle of least privilege | 9.4 | 0 | 2 |
| game testing | 9.4 | 0 | 2 |
| Supply chain risk management | 9.4 | 0 | 2 |
| intelligent agent | 9.4 | 0 | 2 |
| Cyc | 9.4 | 0 | 2 |
| corporate governance of information technology | 9.4 | 0 | 2 |
| data lineage | 9.4 | 0 | 2 |
| water quality management | 9.4 | 0 | 2 |
| Emerson Electric | 9.4 | 0 | 2 |
| machine vision | 9.4 | 0 | 2 |
| commonsense knowledge base | 9.4 | 0 | 2 |
| International Journal of Computer Vision | 9.4 | 0 | 2 |
| role-based access control | 9.4 | 0 | 2 |
| Metro by T-Mobile | 9.4 | 0 | 2 |
| sentiment analysis | 9.4 | 0 | 2 |
| evidence-based practice | 9.4 | 0 | 2 |
| Decision Intelligence | 9.4 | 0 | 2 |
| Andrei Broder | 9.4 | 0 | 2 |
| David M. Blei | 9.4 | 0 | 2 |
| concept drift | 9.4 | 0 | 2 |
| Pierre Baldi | 9.4 | 0 | 2 |
| grid search | 9.4 | 0 | 2 |
| Graph cuts in computer vision | 9.4 | 0 | 2 |
| training, validation, and test data sets | 9.4 | 0 | 2 |
| Trusted Network Connect | 9.4 | 0 | 2 |
| access management | 9.4 | 0 | 2 |
| Andrew McCallum | 9.4 | 0 | 2 |
| business process automation | 9.4 | 0 | 2 |
| Calculating demand forecast accuracy | 9.4 | 0 | 2 |
| Chauncey Starr | 9.4 | 0 | 2 |
| Commission on Risk Assessment and Risk Management | 9.4 | 0 | 2 |
| Daniel S. Jurafsky | 9.4 | 0 | 2 |
| Distributed Access Control System | 9.4 | 0 | 2 |
| early stopping | 9.4 | 0 | 2 |
| Eric Horvitz | 9.4 | 0 | 2 |
| geometric feature learning | 9.4 | 0 | 2 |
| go-to-market strategy | 9.4 | 0 | 2 |
| Journal of Artificial Intelligence Research | 9.4 | 0 | 2 |
| Journal of Product Innovation Management | 9.4 | 0 | 2 |
| Ken Forbus | 9.4 | 0 | 2 |
| Kevin Leyton-Brown | 9.4 | 0 | 2 |
| Manufacturing & Service Operations Management | 9.4 | 0 | 2 |
| Piotr Indyk | 9.4 | 0 | 2 |
| Sherwood Applied Business Security Architecture | 9.4 | 0 | 2 |
| statistical relational learning | 9.4 | 0 | 2 |
| Supplier Quality Assurance | 9.4 | 0 | 2 |
| Quality Assurance Journal | 9.4 | 0 | 2 |
| Applied Artificial Intelligence | 9.4 | 0 | 2 |
| Quality Management Journal | 9.4 | 0 | 2 |
| Connection Science | 9.4 | 0 | 2 |
| Statistical Analysis and Data Mining | 9.4 | 0 | 2 |
| Journal of Experimental and Theoretical Artificial Intelligence | 9.4 | 0 | 2 |
| The Journal of Change Management | 9.4 | 0 | 2 |
| Natural Language Engineering | 9.4 | 0 | 2 |
| Moses Charikar | 9.4 | 0 | 2 |
| Lise Getoor | 9.4 | 0 | 2 |
| Lenhart Schubert | 9.4 | 0 | 2 |
| Tree kernel | 9.4 | 0 | 2 |
| ISO/IEC 31010 | 9.4 | 0 | 2 |
| similarity learning | 9.4 | 0 | 2 |
| cybersecurity | 9.4 | 0 | 2 |
| vanishing gradient problem | 9.4 | 0 | 2 |
| Michael J. Kearns | 9.4 | 0 | 2 |
| J. Nathan Kutz | 9.4 | 0 | 2 |
| AHaH Computing–From Metastable Switches to Attractors to Machine Learning | 9.4 | 0 | 2 |
| Dan Roth | 9.4 | 0 | 2 |
| feature engineering | 9.4 | 0 | 2 |
| RankBrain | 9.4 | 0 | 2 |
| Risk Assessment and Risk Management of Nanomaterials in the Workplace: Translating Research to Practice | 9.4 | 0 | 2 |
| Nervana Systems | 9.4 | 0 | 2 |
| A public health context for residual risk assessment and risk management under the clean air act | 9.4 | 0 | 2 |
| Regina Barzilay | 9.4 | 0 | 2 |
| Data quality assurance and quality control measures in large multicenter stroke trials: the African-American Antiplatelet Stroke Prevention Study experience | 9.4 | 0 | 2 |
| Launching total quality management in the Bureau of Mines: a case study. Quality improvement report: October 1990 through September 1992 | 9.4 | 0 | 2 |
| Recommendations on Quality Control and Quality Assurance in Cervical Cytology | 9.4 | 0 | 2 |
| Machine Learning Methods in Systematic Reviews: Identifying Quality Improvement Intervention Evaluations | 9.4 | 0 | 2 |
| Eduard Hovy | 9.4 | 0 | 2 |
| eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment | 9.4 | 0 | 2 |
| High-throughput analysis of behavior for drug discovery | 9.4 | 0 | 2 |
| Quality assurance and utilization review : official journal of the American College of Utilization Review Physicians | 9.4 | 0 | 2 |
| Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition | 9.4 | 0 | 2 |
| Tommi S. Jaakkola | 9.4 | 0 | 2 |
| A multidisciplinary approach to therapeutic risk management of the suicidal patient | 9.4 | 0 | 2 |
| Probabilistic machine learning and artificial intelligence | 9.4 | 0 | 2 |
| artificial intelligence in healthcare | 9.4 | 0 | 2 |
| Rogue Fitness | 9.4 | 0 | 2 |
| Quality Control Measures over 30 Years in a Multicenter Clinical Study: Results from the Diabetes Control and Complications Trial / Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study | 9.4 | 0 | 2 |
| CRFs based de-identification of medical records | 9.4 | 0 | 2 |
| Automatic de-identification of electronic medical records using token-level and character-level conditional random fields | 9.4 | 0 | 2 |
| Privacy, Security, and Patient Engagement: The Changing Health Data Governance Landscape | 9.4 | 0 | 2 |
| How Compliance Measures, Behavior Modification, and Continuous Quality Improvement Led to Routine HIV Screening in an Emergency Department in Brooklyn, New York | 9.4 | 0 | 2 |
| Detection of sentence boundaries and abbreviations in clinical narratives | 9.4 | 0 | 2 |
| Challenges and Practical Approaches with Word Sense Disambiguation of Acronyms and Abbreviations in the Clinical Domain | 9.4 | 0 | 2 |
| Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision | 9.4 | 0 | 2 |
| Learning classification models with soft-label information | 9.4 | 0 | 2 |
| Synthesis lectures on artificial intelligence and machine learning | 9.4 | 0 | 2 |
| Alec Radford | 9.4 | 0 | 2 |
| Arthur Zimek | 9.4 | 0 | 2 |
| Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer’s Disease Stigma on Twitter | 9.4 | 0 | 2 |
| Quality improvement versus quality assurance? | 9.4 | 0 | 2 |
| The cost of quality assurance/quality control | 9.4 | 0 | 2 |
| Integrating total quality management and quality assurance at the University of Michigan Medical Center | 9.4 | 0 | 2 |
| A global machine learning based scoring function for protein structure prediction | 9.4 | 0 | 2 |
| PCP-ML: Protein characterization package for machine learning | 9.4 | 0 | 2 |
| Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises | 9.4 | 0 | 2 |
| Improving organisational resilience through enterprise security risk management | 9.4 | 0 | 2 |
| How to use continuous quality improvement theory and statistical quality control tools in a multispecialty clinic | 9.4 | 0 | 2 |
| Use of total quality management sparks staff nurse participation in continuous quality improvement. | 9.4 | 0 | 2 |
| Quality improvement: how does it differ from quality assurance? | 9.4 | 0 | 2 |
| From quality assurance to continuous quality improvement in the American health care system. Personal experiences gained through a 3-week educational stay | 9.4 | 0 | 2 |
| Detecting Falls with Wearable Sensors Using Machine Learning Techniques | 9.4 | 0 | 2 |
| Process Evaluation of an Open Architecture Real-Time Molecular Laboratory Platform | 9.4 | 0 | 2 |
| Quality control and quality assurance in genotypic data for genome-wide association studies | 9.4 | 0 | 2 |
| Heat wave hazard classification and risk assessment using artificial intelligence fuzzy logic | 9.4 | 0 | 2 |
| From quality assurance to quality management. Applying data from quality assurance studies | 9.4 | 0 | 2 |
| Data governance frameworks and change management | 9.4 | 0 | 2 |
| Application of machine learning algorithms for clinical predictive modeling: a data-mining approach in SCT | 9.4 | 0 | 2 |
| Automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of planning CT and FDG-PET/CT images | 9.4 | 0 | 2 |
| The use of quantitative histological and molecular data for risk assessment and biologically based model development | 9.4 | 0 | 2 |
| Fusing Dual-Event Data Sets for Mycobacterium tuberculosis Machine Learning Models and Their Evaluation | 9.4 | 0 | 2 |
| Quality assurance and quality control data validation procedures used for the Love Canal and Dallas lead soil monitoring programs | 9.4 | 0 | 2 |
| Integrating machine learning techniques into robust data enrichment approach and its application to gene expression data | 9.4 | 0 | 2 |
| Evaluation of various machine learning methods to predict vision-related quality of life from visual field data and visual acuity in patients with glaucoma | 9.4 | 0 | 2 |
| Transfer learning based clinical concept extraction on data from multiple sources | 9.4 | 0 | 2 |
| Are Bigger Data Sets Better for Machine Learning? Fusing Single-Point and Dual-Event Dose Response Data for Mycobacterium tuberculosis | 9.4 | 0 | 2 |
| Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach | 9.4 | 0 | 2 |
| Semantically-based priors and nuanced knowledge core for Big Data, Social AI, and language understanding | 9.4 | 0 | 2 |
| Analysis of cytokine release assay data using machine learning approaches | 9.4 | 0 | 2 |
| Applications of Machine Learning and Data Mining Methods to Detect Associations of Rare and Common Variants with Complex Traits | 9.4 | 0 | 2 |
| In-house daily consensus conference: an important quality control/quality assurance activity--experience at a major referral center | 9.4 | 0 | 2 |
| An integrated organisation-wide data quality management and information governance framework: theoretical underpinnings | 9.4 | 0 | 2 |
| "Big data" - large data, a lot of knowledge? | 9.4 | 0 | 2 |
| Anomaly detection based on sensor data in petroleum industry applications | 9.4 | 0 | 2 |
| Assessing the fit of biotic ligand model validation data in a risk management decision context | 9.4 | 0 | 2 |
| Frank Pasquale | 9.4 | 0 | 2 |
| Performance-based medicine drives data governance. Analytics spur efforts to ensure purity, consistency of data | 9.4 | 0 | 2 |
| Integrating risk management data in quality improvement initiatives within an academic neurosurgery department | 9.4 | 0 | 2 |
| Assessing the Impact of Blood Loss in Cranial Vault Remodeling: A Risk Assessment Model Using the 2012 to 2013 Pediatric National Surgical Quality Improvement Program Data Sets | 9.4 | 0 | 2 |
| Discussion: Assessing the Impact of Blood Loss in Cranial Vault Remodeling: A Risk Assessment Model Using the 2012 to 2013 Pediatric National Surgical Quality Improvement Program Data Sets | 9.4 | 0 | 2 |
| Quality Assurance Implications of Federal Peer Review Laws: The Health Care Quality Improvement Act and the National Practitioner Data Bank | 9.4 | 0 | 2 |
| Quality control and assurance in hematopoietic stem cell transplantation data registries in Japan and other countries | 9.4 | 0 | 2 |
| Reducing security risk using data loss prevention technology | 9.4 | 0 | 2 |
| Providing data science support for systems pharmacology and its implications to drug discovery | 9.4 | 0 | 2 |
| Cancer risk assessment for 1,3-butadiene: data integration opportunities | 9.4 | 0 | 2 |
| A Hierarchical Classification and Segmentation Scheme for Processing Sensor Data | 9.4 | 0 | 2 |
| Fall risk assessment through automatic combination of clinical fall risk factors and body-worn sensor data | 9.4 | 0 | 2 |
| Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines | 9.4 | 0 | 2 |
| Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction | 9.4 | 0 | 2 |
| Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures | 9.4 | 0 | 2 |
| Big Data, Predictive Analytics, and Quality Improvement in Kidney Transplantation: A Proof of Concept | 9.4 | 0 | 2 |
| Twelve tips for turning quality assurance data into undergraduate teaching awards: A quality improvement and student engagement initiative. | 9.4 | 0 | 2 |
| A review on machine learning principles for multi-view biological data integration | 9.4 | 0 | 2 |
| Real-time monitoring data for real-time multi-model validation: coupling ENSEMBLE and EURDEP. | 9.4 | 0 | 2 |
| Continuous monitoring of regional cerebral blood flow: experimental and clinical validation of a novel thermal diffusion microprobe | 9.4 | 0 | 2 |
| The Quality Assurance Project: introducing quality improvement to primary health care in less developed countries | 9.4 | 0 | 2 |
| Cross-platform comparison of SYBR Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC) study | 9.4 | 0 | 2 |
| Improving data quality control in quality improvement projects | 9.4 | 0 | 2 |
| The impact of the International Atomic Energy Agency (IAEA) program on radiation and tissue banking in Uruguay: development of tissues quality control and quality management system in the National Multi-Tissue Bank of Uruguay | 9.4 | 0 | 2 |
| Architecture, cost-model and customization of real-time monitoring systems based on mobile biological sensor data-streams | 9.4 | 0 | 2 |
| Text-mining of PubMed abstracts by natural language processing to create a public knowledge base on molecular mechanisms of bacterial enteropathogens | 9.4 | 0 | 2 |
| Quality assurance by routine data (QAR)--a new dimension in quality management of inpatient treatment? | 9.4 | 0 | 2 |
| The Integrated Oncology Program of the Italian Ministry of Health. Analytical and clinical validation of new biomarkers for early diagnosis: network, resources, methodology, quality control, and data analysis | 9.4 | 0 | 2 |
| Using the web for recruitment, screen, tracking, data management, and quality control in a dietary assessment clinical validation trial | 9.4 | 0 | 2 |
| Quality assurance and quality control in light stable isotope laboratories: A case study of Rio Grande, Texas, water samples | 9.4 | 0 | 2 |
| Internal quality control and external quality assurance in the IVF laboratory | 9.4 | 0 | 2 |
| Quality improvement and quality assurance compared | 9.4 | 0 | 2 |
| Quality assurance and quality improvement: the 1990s and beyond | 9.4 | 0 | 2 |
| Development of a continuous quality improvement/total quality management program for medication use monitoring. | 9.4 | 0 | 2 |
| From quality assurance to continuous quality improvement | 9.4 | 0 | 2 |
| Informatics, imaging, and healthcare quality management: imaging quality improvement opportunities and lessons learned form HCFA's Health Care Quality Improvement Program | 9.4 | 0 | 2 |
| Case management as a force for quality assurance and quality improvement in home care | 9.4 | 0 | 2 |
| Consultant services in quality assurance and risk management | 9.4 | 0 | 2 |
| Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients. | 9.4 | 0 | 2 |
| Healthcare chains - enabling application and data privacy controls for healthcare information systems | 9.4 | 0 | 2 |
| Quality management for the processing of medical devices | 9.4 | 0 | 2 |
| Assessing the impact of continuous quality improvement/total quality management: concept versus implementation | 9.4 | 0 | 2 |
| Recombinant human G6PD for quality control and quality assurance of novel point-of-care diagnostics for G6PD deficiency | 9.4 | 0 | 2 |
| Processing of wearable sensor data on the cloud - a step towards scaling of continuous monitoring of health and well-being | 9.4 | 0 | 2 |
| How changing quality management influenced PGME accreditation: a focus on decentralization and quality improvement. | 9.4 | 0 | 2 |
| Managing the unmanageable: risk assessment and risk management in contemporary professional practice | 9.4 | 0 | 2 |
| Risk assessment and risk management implications of hormesis | 9.4 | 0 | 2 |
| Trends in risk assessment and risk management | 9.4 | 0 | 2 |
| Risk management and quality improvement: together at last--Part 2. | 9.4 | 0 | 2 |
| Developments in professional quality assurance towards quality improvement: some examples of peer review in the Netherlands and the United Kingdom | 9.4 | 0 | 2 |
| Ability of laboratories to detect emerging antimicrobial resistance: proficiency testing and quality control results from the World Health Organization's external quality assurance system for antimicrobial susceptibility testing | 9.4 | 0 | 2 |
| Quality control and quality assurance of platelet counting | 9.4 | 0 | 2 |
| The Conduct of Quality Control and Quality Assurance Testing for PoCT Outside the Laboratory | 9.4 | 0 | 2 |
| Computational identification of surrogate genes for prostate cancer phases using machine learning and molecular network analysis | 9.4 | 0 | 2 |
| Ecotoxicological effects of ciprofloxacin on freshwater species: data integration and derivation of toxicity thresholds for risk assessment | 9.4 | 0 | 2 |
| RNA-SeQC: RNA-seq metrics for quality control and process optimization | 9.4 | 0 | 2 |
| Evolution of Quality Review Programs for Medicare: Quality Assurance to Quality Improvement | 9.4 | 0 | 2 |
| From Risk Assessment to Risk Management: Matching Interventions to Adolescent Offenders' Strengths and Vulnerabilities | 9.4 | 0 | 2 |
| The Role of Toxicological Science in Risk Assessment and Risk Management | 9.4 | 0 | 2 |
| Quality management and quality assurance in haemophilia care: a model at the Bonn haemophilia centre | 9.4 | 0 | 2 |
| Implementing clinical governance in English primary care groups/trusts: reconciling quality improvement and quality assurance | 9.4 | 0 | 2 |
| Risk management and quality assurance: integration for optimal effectiveness | 9.4 | 0 | 2 |
| A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation | 9.4 | 0 | 2 |
| Quality assurance and quality control for biopharmaceutical products | 9.4 | 0 | 2 |
| AISO: Annotation of Image Segments with Ontologies | 9.4 | 0 | 2 |
| Combining Phylogenetic Profiling-Based and Machine Learning-Based Techniques to Predict Functional Related Proteins | 9.4 | 0 | 2 |
| Semi-supervised learning of causal relations in biomedical scientific discourse | 9.4 | 0 | 2 |
| Alzheimer's disease risk assessment using large-scale machine learning methods | 9.4 | 0 | 2 |
| DR-Predictor: Incorporating Flexible Docking with Specialized Electronic Reactivity and Machine Learning Techniques to Predict CYP-Mediated Sites of Metabolism | 9.4 | 0 | 2 |
| Merging risk management and quality assurance in ambulatory HIV care: part 1, the process | 9.4 | 0 | 2 |
| Comparison and combination of several MeSH indexing approaches | 9.4 | 0 | 2 |
| A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli | 9.4 | 0 | 2 |
| Efficient design of meganucleases using a machine learning approach | 9.4 | 0 | 2 |
| Evolution of quality management: integration of quality assurance functions into operations, or "quality is everyone's responsibility". | 9.4 | 0 | 2 |
| COSEHC global vascular risk management quality improvement program: rationale and design | 9.4 | 0 | 2 |
| Prediction of hepatitis C virus interferon/ribavirin therapy outcome based on viral nucleotide attributes using machine learning algorithms | 9.4 | 0 | 2 |
| Avoiding the quality assurance boondoggle in drug treatment programs through total quality management | 9.4 | 0 | 2 |
| In Silico Machine Learning Methods in Drug Development | 9.4 | 0 | 2 |
| Quality assurance and continuous quality improvement: history, current practice, and future directions | 9.4 | 0 | 2 |
| Quality assurance and continuous quality improvement programs for vascular access care. | 9.4 | 0 | 2 |
| Quality assurance and quality improvement using supportive supervision in a large-scale STI intervention with sex workers, men who have sex with men/transgenders and injecting-drug users in India | 9.4 | 0 | 2 |
| Exploring Spanish health social media for detecting drug effects | 9.4 | 0 | 2 |
| Achieving the Health Care Financing Administration limits by quality improvement and quality control. A real-world example | 9.4 | 0 | 2 |
| The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs | 9.4 | 0 | 2 |
| Quality assurance through quality improvement and professional development in the National Breast and Cervical Cancer Early Detection Program | 9.4 | 0 | 2 |
| Challenges in clinical natural language processing for automated disorder normalization | 9.4 | 0 | 2 |
| Extending the evaluation of Genia Event task toward knowledge base construction and comparison to Gene Regulation Ontology task | 9.4 | 0 | 2 |
| A Frequency-based Strategy of Obtaining Sentences from Clinical Data Repository for Crowdsourcing | 9.4 | 0 | 2 |
| Aspects of risk assessment and risk management of nosocomial transmission of classical and variant Creutzfeldt-Jakob disease with special attention to German regulations | 9.4 | 0 | 2 |
| Assessing the outcome of Strengthening Laboratory Management Towards Accreditation (SLMTA) on laboratory quality management system in city government of Addis Ababa, Ethiopia | 9.4 | 0 | 2 |
| New tools for NTD vaccines: A case study of quality control assays for product development of the human hookworm vaccine Na-APR-1M74 | 9.4 | 0 | 2 |
| Fullrmc, a rigid body Reverse Monte Carlo modeling package enabled with machine learning and artificial intelligence | 9.4 | 0 | 2 |
| Can Systematic Reviews Inform GMO Risk Assessment and Risk Management? | 9.4 | 0 | 2 |
| Natural language processing in psychiatry. Artificial intelligence technology and psychopathology | 9.4 | 0 | 2 |
| Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning. | 9.4 | 0 | 2 |
| Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants | 9.4 | 0 | 2 |
| Current approaches to cyanotoxin risk assessment and risk management around the globe | 9.4 | 0 | 2 |
| Feature engineering combined with machine learning and rule-based methods for structured information extraction from narrative clinical discharge summaries | 9.4 | 0 | 2 |
| Machine Learning Algorithms Outperform Conventional Regression Models in Predicting Development of Hepatocellular Carcinoma | 9.4 | 0 | 2 |
| From quality assurance to quality improvement. The Joint Commission on Accreditation of Healthcare Organizations and Emergency Care | 9.4 | 0 | 2 |
| The quality assurance-risk management interface. | 9.4 | 0 | 2 |
| Distributed and Modular CAN-Based Architecture for Hardware Control and Sensor Data Integration | 9.4 | 0 | 2 |
| The health care quality improvement initiative. A new approach to quality assurance in Medicare | 9.4 | 0 | 2 |
| Quality assurance in nuclear medicine--biological quality control of radiopharmaceuticals. | 9.4 | 0 | 2 |
| 100% rapid rescreening for quality assurance in a quality control program in a public health cytologic laboratory | 9.4 | 0 | 2 |
| Risk assessment and risk management of noncriteria pollutants | 9.4 | 0 | 2 |
| Unsupervised Topic Modeling in a Large Free Text Radiology Report Repository | 9.4 | 0 | 2 |
| Clinical Governance: from clinical risk management to continuous quality improvement | 9.4 | 0 | 2 |
| Stability of mean values of organic analytes in lyophilized quality control serum. A study utilizing data from the Quality Assurance Service (QAS) Program of the College of American Pathologists | 9.4 | 0 | 2 |
| Risk Assessment and Hierarchical Risk Management of Enterprises in Chemical Industrial Parks Based on Catastrophe Theory | 9.4 | 0 | 2 |
| Local air quality management as a risk management process: assessing, managing and remediating the risk of exceeding an air quality objective in Great Britain. | 9.4 | 0 | 2 |
| A Natural Language Interface Concordant with a Knowledge Base | 9.4 | 0 | 2 |
| Quality control of agar diffusion susceptibility tests: data from the Quality Assurance Service Microbiology program of the College of American Pathologists | 9.4 | 0 | 2 |
| Model Development for Risk Assessment of Driving on Freeway under Rainy Weather Conditions | 9.4 | 0 | 2 |
| Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx | 9.4 | 0 | 2 |
| Predicting Health Care Utilization After Behavioral Health Referral Using Natural Language Processing and Machine Learning | 9.4 | 0 | 2 |
| Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods | 9.4 | 0 | 2 |
| Stability of mean assay values of magnesium and iron in lyophilized quality control serum: a study based on data from the quality assurance service (QAS) of the College of American Pathologists | 9.4 | 0 | 2 |
| Quality control of agar diffusion susceptibility tests. Data from the Quality Assurance Service Microbiology Program of the College of American Pathologists. | 9.4 | 0 | 2 |
| Use of incidence report data in a system-wide quality assurance/risk management program. | 9.4 | 0 | 2 |
| Long-term stability of glucose in lyophilized quality control serum. A study utilizing data from the Quality Assurance Service (QAS) Program of the College of American Pathologists | 9.4 | 0 | 2 |
| Glucose stability in lyophilized chemistry quality control serum. A study of data from the quality assurance service (QAS) program of the College of American Pathologists | 9.4 | 0 | 2 |
| Stability of sodium and potassium in lyophilized quality control serum. A study of data from the Quality Assurance Service Program of the College of American Pathologists | 9.4 | 0 | 2 |
| Risk Assessment/Risk Management of Motor Vehicle Emissions | 9.4 | 0 | 2 |
| Assessment of Clinical Risk Management System in Hospitals: An Approach for Quality Improvement. | 9.4 | 0 | 2 |
| Sample Confirmation Testing: A Short Tandem Repeat-Based Quality Assurance and Quality Control Procedure for the eyeGENE Biorepository | 9.4 | 0 | 2 |
| Risk management in laboratory medicine: quality assurance programs and professional competence. | 9.4 | 0 | 2 |
| Clinical Evaluation of a Novel and Mobile Autism Risk Assessment | 9.4 | 0 | 2 |
| Methodological Issues in Predicting Pediatric Epilepsy Surgery Candidates Through Natural Language Processing and Machine Learning | 9.4 | 0 | 2 |
| General introduction to risk assessment and risk management | 9.4 | 0 | 2 |
| Lillian Lee | 9.4 | 0 | 2 |
| Men having sex with men donor deferral risk assessment: an analysis using risk management principles | 9.4 | 0 | 2 |
| Discussion on the boundary of risk assessment and risk management | 9.4 | 0 | 2 |
| Quality assurance/quality control procedures for the determination of polychlorinated dibenzodioxins, dibenzofurans and biphenyls | 9.4 | 0 | 2 |
| The COSEHC™ Global Vascular Risk Management quality improvement program: first follow-up report | 9.4 | 0 | 2 |
| Quality assurance and quality control in the laboratory andrology | 9.4 | 0 | 2 |
| Risk management and risk assessment of novel plant foods: concepts and principles. | 9.4 | 0 | 2 |
| Quality assurance and quality improvement: a PACU focus | 9.4 | 0 | 2 |
| Sharing risk management: an implementation model for cardiovascular absolute risk assessment and management in Australian general practice | 9.4 | 0 | 2 |
| Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes | 9.4 | 0 | 2 |
| Quality assurance and quality control in mammography: a review of available guidance worldwide | 9.4 | 0 | 2 |
| A robust conversion method of radioactivities between plastic and NaI scintillation well counters for long-term quality control and quality assurance | 9.4 | 0 | 2 |
| Designing for Risk Assessment Systems for Patient Triage in Primary Health Care: A Literature Review | 9.4 | 0 | 2 |
| Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems | 9.4 | 0 | 2 |
| Internal quality assurance in a clinical virology laboratory. II. Internal quality control | 9.4 | 0 | 2 |
| Automated analysis of retinal imaging using machine learning techniques for computer vision | 9.4 | 0 | 2 |
| Omnibus Risk Assessment via Accelerated Failure Time Kernel Machine Modeling | 9.4 | 0 | 2 |
| Quality assurance to quality improvement: measuring and monitoring pharmaceutical care | 9.4 | 0 | 2 |
| Machine Learning Analysis of the Relationship Between Changes in Immunological Parameters and Changes in Resistance to Listeria monocytogenes: A New Approach for Risk Assessment and Systems Immunology | 9.4 | 0 | 2 |
| Internal quality control and external quality assurance of platelet function tests | 9.4 | 0 | 2 |
| Health benefits of 'grow your own' food in urban areas: implications for contaminated land risk assessment and risk management? | 9.4 | 0 | 2 |
| A Method for the Evaluation of Image Quality According to the Recognition Effectiveness of Objects in the Optical Remote Sensing Image Using Machine Learning Algorithm | 9.4 | 0 | 2 |
| Towards improving cardiovascular risk management in patients with rheumatoid arthritis: the need for accurate risk assessment | 9.4 | 0 | 2 |
| Risk management and quality assurance in the emergency room | 9.4 | 0 | 2 |
| Information extraction from multi-institutional radiology reports | 9.4 | 0 | 2 |
| Intravenous immunoglobulin G: trends in production methods, quality control and quality assurance | 9.4 | 0 | 2 |
| Software-assisted spine registered nurse care coordination and patient triage--one organization's approach | 9.4 | 0 | 2 |
| Medical decision support using machine learning for early detection of late-onset neonatal sepsis | 9.4 | 0 | 2 |
| Response to Achieving cost control, care coordination, and quality improvement through incremental payment system reform | 9.4 | 0 | 2 |
| Maryland's approach in enhancing effectiveness and efficiency in healthcare delivery: comment on "Achieving cost control, care coordination, and quality improvement through incremental payment system reform". | 9.4 | 0 | 2 |
| Optimization on machine learning based approaches for sentiment analysis on HPV vaccines related tweets | 9.4 | 0 | 2 |
| The Effect of 5S-Continuous Quality Improvement-Total Quality Management Approach on Staff Motivation, Patients' Waiting Time and Patient Satisfaction with Services at Hospitals in Uganda | 9.4 | 0 | 2 |
| Patient Safety and Quality Improvement: Medical Errors and Adverse Events | 9.4 | 0 | 2 |
| Evaluating the Medical Evidence for Quality Improvement | 9.4 | 0 | 2 |
| A Strategy to Establish a Quality Assurance/Quality Control Plan for the Application of Biosensors for the Detection of E. coli in Water | 9.4 | 0 | 2 |
| Quality assurance and quality control of thrombelastography and rotational Thromboelastometry: the UK NEQAS for blood coagulation experience | 9.4 | 0 | 2 |
| A Quality Improvement Program Combining Maximal Barrier Precaution Compliance Monitoring and Daily Chlorhexidine Gluconate Baths Resulting in Decreased Central Line Bloodstream Infections | 9.4 | 0 | 2 |
| Liquid-based Papanicolaou tests in endometrial carcinoma diagnosis. Performance, error root cause analysis, and quality improvement | 9.4 | 0 | 2 |
| Successful risk assessment may not always lead to successful risk control: A systematic literature review of risk control after root cause analysis. | 9.4 | 0 | 2 |
| Internal quality control and external quality assurance in testing for antiphospholipid antibodies: Part II--Lupus anticoagulant | 9.4 | 0 | 2 |
| Internal quality control and external quality assurance in testing for antiphospholipid antibodies: Part I--Anticardiolipin and anti-β2-glycoprotein I antibodies | 9.4 | 0 | 2 |
| Research on risk assessment and risk management: future directions | 9.4 | 0 | 2 |
| Travel risk assessment and risk management | 9.4 | 0 | 2 |
| Quality assurance and quality control in the routine molecular diagnostic laboratory for infectious diseases | 9.4 | 0 | 2 |
| From quality assurance to quality improvement. | 9.4 | 0 | 2 |
| Neurological registry quality control and quality assurance | 9.4 | 0 | 2 |
| Quality assurance and quality control for radiotherapy/medical oncology in Europe: guideline development and implementation. | 9.4 | 0 | 2 |
| Therapeutic risk management of the suicidal patient: augmenting clinical suicide risk assessment with structured instruments | 9.4 | 0 | 2 |
| Review of machine learning and signal processing techniques for automated electrode selection in high-density microelectrode arrays | 9.4 | 0 | 2 |
| Machine Learning and Tubercular Drug Target Recognition | 9.4 | 0 | 2 |
| Considering Context in Quality Improvement Interventions and Implementation: Concepts, Frameworks, and Application | 9.4 | 0 | 2 |
| Quality Improvement in Pediatric Emergency Medicine | 9.4 | 0 | 2 |
| Analysis of MicroRNA Expression Using Machine Learning | 9.4 | 0 | 2 |
| Measuring Endoscopic Performance for Colorectal Cancer Prevention Quality Improvement in a Gastroenterology Practice | 9.4 | 0 | 2 |
| Predicting essential genes for identifying potential drug targets in Aspergillus fumigatus | 9.4 | 0 | 2 |
| Class probability estimation for medical studies | 9.4 | 0 | 2 |
| Quantification of the impact of multifaceted initiatives intended to improve operational efficiency and the safety culture: A case study from an academic medical center radiation oncology department | 9.4 | 0 | 2 |
| Wake Up Safe and root cause analysis: quality improvement in pediatric anesthesia | 9.4 | 0 | 2 |
| Machine Learning-Based Methods for Prediction of Linear B-Cell Epitopes | 9.4 | 0 | 2 |
| Suicide risk assessment and suicide risk formulation: essential components of the therapeutic risk management model | 9.4 | 0 | 2 |
| Orally Inhaled Drug Performance Testing for Product Development, Registration, and Quality Control | 9.4 | 0 | 2 |
| Hybrid Machine Learning Technique for Forecasting Dhaka Stock Market Timing Decisions | 9.4 | 0 | 2 |
| Version 3 of the Historical‐Clinical‐Risk Management‐20 (HCR‐20V3): Relevance to Violence Risk Assessment and Management in Forensic Conditional Release Contexts | 9.4 | 0 | 2 |
| An ecosystem services approach to pesticide risk assessment and risk management of non-target terrestrial plants: recommendations from a SETAC Europe workshop | 9.4 | 0 | 2 |
| Improving rates of cotrimoxazole prophylaxis in resource-limited settings: implementation of a quality improvement approach | 9.4 | 0 | 2 |
| Advanced Practice Quality Improvement: Beyond the Radiology Department | 9.4 | 0 | 2 |
| Satellite Data and Machine Learning for Weather Risk Management and Food Security | 9.4 | 0 | 2 |
| Machine Learning in the Rational Design of Antimicrobial Peptides | 9.4 | 0 | 2 |
| Potential Application of Machine Learning in Health Outcomes Research and Some Statistical Cautions | 9.4 | 0 | 2 |
| The application of machine learning to the modelling of percutaneous absorption: An overview and guide | 9.4 | 0 | 2 |
| Simple interventions can greatly improve clinical documentation: a quality improvement project of record keeping on the surgical wards at a district general hospital | 9.4 | 0 | 2 |
| Risk assessment of sewer condition using artificial intelligence tools: application to the SANEST sewer system. | 9.4 | 0 | 2 |
| An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining | 9.4 | 0 | 2 |
| Automated Learning of Temporal Expressions | 9.4 | 0 | 2 |
| Automatically Expanding the Synonym Set of SNOMED CT using Wikipedia | 9.4 | 0 | 2 |
| A new approach for cleansing geographical dataset using Levenshtein distance, prior knowledge and contextual information | 9.4 | 0 | 2 |
| The Mutual Inspirations of Machine Learning and Neuroscience | 9.4 | 0 | 2 |
| Arranging ISO 13606 archetypes into a knowledge base | 9.4 | 0 | 2 |
| Arranging ISO 13606 archetypes into a knowledge base using UML connectors | 9.4 | 0 | 2 |
| Frame semantics-based study of verbs across medical genres | 9.4 | 0 | 2 |
| Does SNOMED CT post-coordination scale? | 9.4 | 0 | 2 |
| What's in a class? Lessons learnt from the ICD - SNOMED CT harmonisation | 9.4 | 0 | 2 |
| The influence of similarity between concepts in evolving biomedical ontologies for mapping adaptation | 9.4 | 0 | 2 |
| Using TimeML to support the modeling of computerized clinical guidelines | 9.4 | 0 | 2 |
| Quality improvement capacity: a survey of hospital quality managers | 9.4 | 0 | 2 |
| Achieving cost control, care coordination, and quality improvement through incremental payment system reform | 9.4 | 0 | 2 |
| Information systems for administration, clinical documentation and quality assurance in an Austrian disease management programme. | 9.4 | 0 | 2 |
| Development of the Dundee Caries Risk Assessment Model (DCRAM)--risk model development using a novel application of CHAID analysis | 9.4 | 0 | 2 |
| Extracting Dependence Relations from Unstructured Medical Text | 9.4 | 0 | 2 |
| Development and evaluation of task-specific NLP framework in China | 9.4 | 0 | 2 |
| Automatic Detection of Skin and Subcutaneous Tissue Infections from Primary Care Electronic Medical Records | 9.4 | 0 | 2 |
| Machine learning applications in genetics and genomics | 9.4 | 0 | 2 |
| Quantifying care coordination using natural language processing and domain-specific ontology | 9.4 | 0 | 2 |
| Exploiting parallel corpora to scale up multilingual biomedical terminologies | 9.4 | 0 | 2 |
| Quality assurance, audit and quality control of radiotherapy at radiology departments in Hungary | 9.4 | 0 | 2 |
| An enhancement of the Role-Based Access Control model to facilitate information access management in context of team collaboration and workflow | 9.4 | 0 | 2 |
| Machine learning methods for the classification of gliomas: Initial results using features extracted from MR spectroscopy | 9.4 | 0 | 2 |
| Quality control review: implementing a scientifically based quality control system | 9.4 | 0 | 2 |
| The impact of transforming healthcare delivery on cystic fibrosis outcomes: a decade of quality improvement at Cincinnati Children’s Hospital | 9.4 | 0 | 2 |
| Commonly Practiced Quality Control and Quality Assurance Procedures for Gas Chromatography-Mass Spectrometry Analysis in Forensic Urine Drug-Testing Laboratories | 9.4 | 0 | 2 |
| Continuous Quality Improvement, Total Quality Management, and Reengineering: One Hospital's Continuous Quality Improvement Journey | 9.4 | 0 | 2 |
| Food and feed chemical contaminants in the European Union: Regulatory, scientific, and technical issues concerning chemical contaminants occurrence, risk assessment, and risk management in the European Union | 9.4 | 0 | 2 |
| Machine Learning approaches on Diagnostic Term Encoding with the ICD for Clinical Documentation | 9.4 | 0 | 2 |
| Investigating the connections between health lean management and clinical risk management | 9.4 | 0 | 2 |
| EMQIT: a machine learning approach for energy based PWM matrix quality improvement | 9.4 | 0 | 2 |
| Violence Risk Assessment and Management in Outpatient Clinical Practice | 9.4 | 0 | 2 |
| Addition of biomarker panel improves prediction performance of American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) calculator for cardiac risk assessment of elderly patients preparing for major non-cardiac surgery: | 9.4 | 0 | 2 |
| Initial clinical validation of Health Heritage, a patient-facing tool for personal and family history collection and cancer risk assessment | 9.4 | 0 | 2 |
| Quality Assurance and Quality Control, Part 2. | 9.4 | 0 | 2 |
| Value of small sample sizes in rapid-cycle quality improvement projects | 9.4 | 0 | 2 |
| Cryopreservation in fish: current status and pathways to quality assurance and quality control in repository development | 9.4 | 0 | 2 |
| Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management | 9.4 | 0 | 2 |
| Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms | 9.4 | 0 | 2 |
| From To Err Is Human to Improving Diagnosis in Health Care: The risk management perspective | 9.4 | 0 | 2 |
| Computer vision for high content screening | 9.4 | 0 | 2 |